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AI · February 23, 2026

TA

TTSLab – A voice AI agent and TTS lab running in the browser via WebGPU

I built TTSLab — a free, open-source tool for running text-to-speech and speech-to-text models directly in the browser using WebGPU and WASM. No API keys, no backend, no data leaves your machine. When you open the site, you'll hear it immediately — the landing page auto-generates speech from three different sentences right in your browser, no setup required. You can then try any model yourself: type text, hit generate, hear it instantly. Models download once and get cached locally. The most experimental feature: a fully in-browser Voice Agent. It chains speech-to-text → LLM → text-to-speech,…

Visit ttslab.devAlternativestop 18% of February 2026

What it does

In the maker’s words, at launch

I built TTSLab — a free, open-source tool for running text-to-speech and speech-to-text models directly in the browser using WebGPU and WASM. No API keys, no backend, no data leaves your machine. When you open the site, you'll hear it immediately — the landing page auto-generates speech from three different sentences right in your browser, no setup required. You can then try any model yourself: type text, hit generate, hear it instantly. Models download once and get cached locally. The most experimental feature: a fully in-browser Voice Agent. It chains speech-to-text → LLM → text-to-speech, all running locally on your GPU via WebGPU. You can have a spoken conversation with an AI without a single network request. Currently supported models: - TTS: Kokoro 82M, SpeechT5, Piper (VITS) - STT: Whisper Tiny, Whisper Base Other features: - Side-by-side model comparison - Speed benchmarking on your hardware - Streaming generation for supported models Source: https://github.com/MbBrainz/ttslab (MIT) Feedback I'd especially like: 1. How does performance feel on your hardware? 2. What models should I add next? 3. Did the Voice Agent work for you? That's the most experimental part. Built on top of ONNX Runtime Web (https://onnxruntime.ai) and Transformers.js — huge thanks to those communities for making in-browser ML inference possible.

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